General position of Croatian medical biochemistry laboratories on autovalidation: survey of the Working Group for Post-analytics of the Croatian Society of Medical Biochemistry and Laboratory Medicine

Introduction Autovalidation (AV) is an algorithm based on predefined rules designed, among others, to automate and standardize the postanalytical phase of laboratory work. The aim of this study was to examine the overall opinion of Croatian medical biochemistry laboratories regarding various aspects of AV. Material and methods This retrospective study is an analysis of the responses of a survey about AV comprised of 18 questions, as part of Module 10 (“Postanalytical phase of laboratory testing”) of national External Quality Assessment program, administered by the Croatian Centre for Quality Assessment in Laboratory Medicine. Results were reported as percentages of total number of participants in survey or as proportions of observed data if the overall number of data was <100. Results 121 laboratories responded to the survey, of which 76% do not use AV, while 11% of laboratories use AV in routine laboratory work. 16/29 laboratories implemented semi-automated AV for general biochemistry (7/29), haematology (5/29), and coagulation (4/29) tests. Analytical measurement ranges, critical values, flags from analysers, interference indices and delta check were the most commonly used rules in the algorithm. 12/29 laboratories performed validation of AV with less than 500 samples (8/29). 7/13 laboratories report the percentage of AV being 20-50%, while 10/13 answered that introduction of AV significantly reduced turnaround time (TAT) (for 20 - 25%), especially for biochemistry tests. Conclusions Despite of its numerous benefits (i.e. shorter TAT, less manual validation, standardization of the postanalytical phase), only a small number of Croatian laboratories use AV.

[1]  L. Onelöv,et al.  Autoverification of routine coagulation assays in a multi-center laboratory , 2016, Scandinavian journal of clinical and laboratory investigation.

[2]  Jan P. Kuijsters LabRespond: a tool for autoverification , 2002 .

[3]  Narayan Torke,et al.  Process improvement and operational efficiency through test result autoverification. , 2005, Clinical chemistry.

[4]  E. Fernández-Grande,et al.  Impact of reference change value (RCV) based autoverification on turnaround time and physician satisfaction , 2017, Biochemia medica.

[5]  Dale J. Duca Autoverification in a Laboratory Information System , 2002 .

[6]  W. Oosterhuis,et al.  Evaluation of LabRespond, a new automated validation system for clinical laboratory test results. , 2000, Clinical chemistry.

[7]  N. Tien,et al.  Building and Validating an Autoverification System in the Clinical Chemistry Laboratory , 2011 .

[8]  Laurent Prost,et al.  How autoverification through the expert system VALAB can make your laboratory more efficient , 2002 .

[9]  Giuseppe Lippi,et al.  Development and implementation of an automatic system for verification, validation and delivery of laboratory test results , 2009, Clinical chemistry and laboratory medicine.

[10]  Bo Qu,et al.  Design and evaluation of a LIS-based autoverification system for coagulation assays in a core clinical laboratory , 2019, BMC Medical Informatics and Decision Making.

[11]  Yingmu Cai,et al.  Establishing and Evaluating Autoverification Rules with Intelligent Guidelines for Arterial Blood Gas Analysis in a Clinical Laboratory , 2018, SLAS technology.

[12]  P. Froom,et al.  Auto-validation of complete blood counts in an outpatient’s regional laboratory , 2015, Clinical chemistry and laboratory medicine.

[13]  Matthew D. Krasowski,et al.  Autoverification in a core clinical chemistry laboratory at an academic medical center , 2014, Journal of pathology informatics.

[14]  Jasna Lenicek Krleza,et al.  Post-analytical laboratory work: national recommendations from the Working Group for Post-analytics on behalf of the Croatian Society of Medical Biochemistry and Laboratory Medicine , 2019, Biochemia medica.

[15]  Jiaxing Wang,et al.  Establishment of the intelligent verification criteria for a routine urinalysis analyzer in a multi-center study , 2019, Clinical chemistry and laboratory medicine.

[16]  R. Zadro,et al.  Autovalidation and automation of the postanalytical phase of routine hematology and coagulation analyses in a university hospital laboratory , 2017, Clinical chemistry and laboratory medicine.

[17]  N. de Jonge,et al.  Automated processing of serum indices used for interference detection by the laboratory information system. , 2005, Clinical chemistry.

[18]  Callum G. Fraser,et al.  Biological variation data are necessary prerequisites for objective autoverification of clinical laboratory data , 2002 .

[19]  D. Rogić,et al.  Implementation of the Autovalidation Algorithm for Clinical Chemistry Testing in the Laboratory Information System , 2018, Laboratory medicine.